3 citations · 3 across the 6 of their papers we have counts for
9 papers
OIL: An Object Interaction Layer for Humanoid Whole-Body Control
Pranay Dugar, Mohitvishnu S. Gadde, Rajesh Mangannavar +2
Recent progress in learned whole-body controllers for humanoid robots has enabled robust free-space motion by tracking kinematic targets such as joint or end-effector trajectories.…
Learning Multi-Humanoid Pickup and Transport via Decentralized Object-Centric Control
Bikram Pandit, Mohitvishnu S. Gadde, Aayam Kumar Shrestha +1
We study cooperative multi-humanoid pickup and transport of objects with varying size, weight, and geometry, requiring robot teams of different sizes. Our approach uses decentraliz…
Collision-Aware Humanoid Whole-Body Control under Imperfect Tracking Targets
Mohitvishnu S. Gadde, Ashish Malik, Pranay Dugar +3
Humanoid robots often execute motion commands through whole-body controllers (WBCs) that track targets while maintaining balance and stability. However, most WBCs are blind to scen…
Grounding Vision and Language to 3D Masks for Long-Horizon Box Rearrangement
Ashish Malik, Caleb Lowe, Aayam Shrestha +3
We study long-horizon planning in 3D environments from under-specified natural-language goals using only visual observations, focusing on multi-step 3D box rearrangement tasks. Exi…
Humanoid Hanoi: Investigating Shared Whole-Body Control for Skill-Based Box Rearrangement
Minku Kim, Kuan-Chia Chen, Aayam Shrestha +3
We introduce \emph{Humanoid Hanoi}, a challenge problem for long-horizon humanoid skill composition that requires a robot to repeatedly sequence pickup, locomotion, and placement s…
Multi-Quadruped Cooperative Object Transport: Learning Decentralized Pinch-Lift-Move
Bikram Pandit, Aayam Kumar Shrestha, Alan Fern
We study decentralized cooperative transport using teams of N-quadruped robots with arm that must pinch, lift, and move ungraspable objects through physical contact alone. Unlike p…
No More Marching: Learning Humanoid Locomotion for Short-Range SE(2) Targets
Pranay Dugar, Mohitvishnu S. Gadde, Jonah Siekmann +3
Humanoids operating in real-world workspaces must frequently execute task-driven, short-range movements to SE(2) target poses. To be practical, these transitions must be fast, robu…
Generating Physically Realistic and Directable Human Motions from Multi-Modal Inputs
Aayam Shrestha, Pan Liu, German Ros +2
This work focuses on generating realistic, physically-based human behaviors from multi-modal inputs, which may only partially specify the desired motion. For example, the input may…
Learning Multi-Modal Whole-Body Control for Real-World Humanoid Robots
Pranay Dugar, Aayam Shrestha, Fangzhou Yu +2
A major challenge in humanoid robotics is designing a unified interface for commanding diverse whole-body behaviors, from precise footstep sequences to partial-body mimicry and joy…